Cover Image

Anomalous Decision Discovery using Inverse Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bastola, Ashish, Pesé, Mert D., Cheng, Long, Smereka, Jonathon, Razi, Abolfazl
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect Communication
by: Bastola, Ashish, et al.
Published: (2025)

Multi-Agent Deep Reinforcement Learning Under Constrained Communications
by: Shaik, Shahil, et al.
Published: (2026)

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control
by: Alzorgan, Hazim, et al.
Published: (2025)

Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehicles
by: Bastola, Ashish, et al.
Published: (2024)

Graph Based Deep Reinforcement Learning Aided by Transformers for Multi-Agent Cooperation
by: Elrod, Michael, et al.
Published: (2025)

FedMIL: Federated-Multiple Instance Learning for Video Analysis with Optimized DPP Scheduling
by: Bastola, Ashish, et al.
Published: (2024)

MA-VLCM: A Vision Language Critic Model for Value Estimation of Policies in Multi-Agent Team Settings
by: Shaik, Shahil, et al.
Published: (2026)

Transforming In-Vehicle Network Intrusion Detection: VAE-based Knowledge Distillation Meets Explainable AI
by: Yagiz, Muhammet Anil, et al.
Published: (2024)

Comparative Analysis of Patch Attack on VLM-Based Autonomous Driving Architectures
by: Fernandez, David, et al.
Published: (2026)

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory
by: Çelikok, Mustafa Mert, et al.
Published: (2024)

Diffusion Prism: Enhancing Diversity and Morphology Consistency in Mask-to-Image Diffusion
by: Wang, Hao, et al.
Published: (2025)

Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
by: Moon, Sang Bin, et al.
Published: (2024)

A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges
by: Liu, Guiliang, et al.
Published: (2024)

Offline Inverse Constrained Reinforcement Learning for Safe-Critical Decision Making in Healthcare
by: Fang, Nan, et al.
Published: (2024)

Cooperative Inverse Reinforcement Learning
by: Hadfield-Menell, Dylan, et al.
Published: (2016)

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models
by: Zhu, Wenhui, et al.
Published: (2025)

Hybrid Inverse Reinforcement Learning
by: Ren, Juntao, et al.
Published: (2024)

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC
by: Clark, Tyler, et al.
Published: (2024)

Reinforcement Learning Compensated Model Predictive Control for Off-road Driving on Unknown Deformable Terrain
by: Gupta, Prakhar, et al.
Published: (2024)

TROFI: Trajectory-Ranked Offline Inverse Reinforcement Learning
by: Sestini, Alessandro, et al.
Published: (2025)

Recursive Deep Inverse Reinforcement Learning
by: Ghanem, Paul, et al.
Published: (2025)

Fast Rates for Inverse Reinforcement Learning
by: Schlaginhaufen, Andreas, et al.
Published: (2026)

On the Effective Horizon of Inverse Reinforcement Learning
by: Xu, Yiqing, et al.
Published: (2023)

Environment Design for Inverse Reinforcement Learning
by: Buening, Thomas Kleine, et al.
Published: (2022)

Inverse Reinforcement Learning With Constraint Recovery
by: Das, Nirjhar, et al.
Published: (2023)

Behaviour Discovery and Attribution for Explainable Reinforcement Learning
by: Rishav, Rishav, et al.
Published: (2025)

Biological Neurons Compete with Deep Reinforcement Learning in Sample Efficiency in a Simulated Gameworld
by: Khajehnejad, Moein, et al.
Published: (2024)

Learning Reasoning Rewards from Expert Demonstrations with Inverse Reinforcement Learning
by: Fanconi, Claudio, et al.
Published: (2025)

Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning
by: Kweider, Leen, et al.
Published: (2024)

Inverse Delayed Reinforcement Learning
by: Zhan, Simon Sinong, et al.
Published: (2024)

Discovering What You Can Control: Interventional Boundary Discovery for Reinforcement Learning
by: Liu, Jiaxin, et al.
Published: (2026)

Symmetry-Guided Multi-Agent Inverse Reinforcement Learning
by: Tian, Yongkai, et al.
Published: (2025)

Is Optimal Transport Necessary for Inverse Reinforcement Learning?
by: Dong, Zixuan, et al.
Published: (2025)

Partial Identifiability and Misspecification in Inverse Reinforcement Learning
by: Skalse, Joar, et al.
Published: (2024)

Inverse Reinforcement Learning with Sub-optimal Experts
by: Poiani, Riccardo, et al.
Published: (2024)

Kernel Density Bayesian Inverse Reinforcement Learning
by: Mandyam, Aishwarya, et al.
Published: (2023)

Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
by: Beliaev, Mark, et al.
Published: (2024)

Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
by: Xie, Sean, et al.
Published: (2022)

Tiny Reinforcement Learning for Quadruped Locomotion using Decision Transformers
by: Akgün, Orhan Eren, et al.
Published: (2024)

Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective
by: Zhao, Lei, et al.
Published: (2023)